AI Readability Grader

Score how easily an AI model can parse and extract facts from your text.

What "AI readability" measures here

Traditional readability formulas (like Flesch-Kincaid) estimate how easy text is for a human to read. This tool instead checks structural signals that make text easier for an AI system to parse and extract facts from when summarizing or citing a page: sentence length, paragraph length, the presence of lists and headings, and passive-voice usage. It is a heuristic estimate based on well-documented content structure best practices, not a connection to any specific AI model's internal behavior.

Why human readability and AI parseability aren't quite the same thing

A human reader can follow a long, winding sentence with the help of tone, inflection, and general world knowledge - but a system extracting discrete facts for a summary tends to do better with short, single-idea sentences it can isolate cleanly. The two goals overlap substantially but aren't identical, which is why this tool checks a distinct (though related) set of structural signals from a traditional human-readability formula.

Why passive voice specifically gets flagged

A sentence like "the cause was identified as X" buries who or what did the identifying, while "researchers identified X as the cause" states it directly - active voice generally makes the actor and the action explicit in a way that's easier to extract as a clean fact, which is why a noticeably high passive-voice ratio lowers this tool's score.

Why question-style lines count toward the score

Framing a section around the exact question a reader (or an AI system matching a query to your page) would ask - "What is X?", "How does X work?" - as its own line gives that section a clear, literal match target. This tool checks for at least one line written as a direct question, since that pattern is one of the more commonly cited structural signals in answer-engine optimization write-ups, alongside headings and lists. It is a cheap, honest proxy for "is this content organized the way an FAQ or Q&A page would be" - not a measure of whether your questions are well-chosen.

Why a perfect score is a structural signal, not a citation guarantee

Whether an AI system actually cites or surfaces a specific page depends on many factors entirely outside text structure - the site's authority, how relevant the content is to a specific query, how fresh it is, and more. This tool checks only whether your content's structure makes it easy to parse if it is considered, which is a necessary condition worth getting right, but not a sufficient one for being cited.

Câu hỏi thường gặp

Is this the same as checking Google ranking factors?

No - this checks structural clarity relevant to how AI answer engines extract and summarize content, which is a different (though related) concern from traditional Google ranking signals.

Does a perfect score guarantee an AI model will cite my page?

No - this tool checks structural readability only. Whether an AI system cites your page also depends on authority, relevance, freshness and many factors entirely outside a text structure check.

Why does this check different things than a traditional readability formula?

Human readers can follow long sentences using tone and context, while a fact-extracting system benefits more from short, single-idea sentences it can isolate cleanly - the two goals overlap but aren't identical.

Why does passive voice lower the score?

Active voice tends to state who or what did something directly, which is easier to extract as a clean fact than passive phrasing that buries the actor - a high passive-voice ratio makes extraction harder.

Why does the tool check for question-style lines?

At least one line written as a direct question (e.g. "What is X?") gives a section a literal match target, similar to how an FAQ page is structured - it's a cheap, commonly cited signal for answer-engine optimization, checked alongside headings and lists.

What should I fix first if my score is low?

Check the breakdown for your weakest component - very long sentences or paragraphs, missing headings, lists or question-style lines, and heavy passive voice are the most common and most fixable contributors to a low score.

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